virtual research environments for implementing long tail open science
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BlueBRIDGE receives funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 675680 www.bluebridge-vres.eu
Virtual Research Environments for implementing Long-tail Open Science
30 September 2016 - Krakow
Pasquale PaganoCNR, [email protected]
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Context
new approaches to collect-analyse-curate the data
New tools to exchange and guarantee the longevity of the data and the reusability of the experiments
Open Science: make scientific research, data and dissemination accessible to all levels of an inquiring society, amateur or professional
Keywords: Open Access, Open Research, Open Notebook Science
Science 2.0: use network technologies to process large data sets and share experimental results and processes using a collaborative approach. Support Reproducibility-Repeatability-Reusability (R-R-R) of Science
Keywords: Provenance of the scientific process and workflows, Collaborative and Repeatable Science
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Long-tail Open Science
• are multidisciplinary, involve members belonging to diverse organisations • require to access data and services that are spread among many providers
dynamically aggregated to address research questions/problems
• cannot rely on pre-organised and costly supporting environments managed by dedicated organizations
build and operate their own supporting environments
wish to effectively inject open science in daily tasks
cost and time required to implement this approach largely exceed the available capacities
Not individual researchers but group of researchers
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Requirements for IT systems
• Support collaborative research and experimentation
• Implement Reproducibility-Repeatability-Reusability
• Allow sharing data and findings
• Grant open access to produced scientific knowledge and data
• Tackle simplified access to existing computing and storage resources
• Ensure low operational and maintenance costs
• Manage heterogeneous data access policies
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Virtual Research Environment
An operational environment
• Where set of resources (data, services, computational, and storage resources)
• are assigned to group of users via interfaces
• for a limited timeframe
L. Candela, D. Castelli, P. Pagano (2013) Virtual Research Environments: An Overview and a Research Agenda. Data Science Journal, Vol. 12
Created on demand
Regulated by tailored policies
No cost for the resource providers
Open to host and operate custom software
VRE Creation
Configuration
ApplicationsMetadata
Data
Simple and effective process to define a new environment
Applications vs Services
Registry
Logi
cal
View
Applications Data
Phys
ical
View
Hardware
Software, Tools, Services
Configuration
Data
The iMarine Use Case
VREs in operation
Data Infrastructures Computing Infrastructures
Mediator Connector Mediator Connector
Data Curation
Data Preparation
Data Analysis
Data Sharing
Data Publication
Data Provenance
VRE Builder
Security
Monitoring
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VREs in operationThe D4Science e-Infrastructure
D4Science supports scientists in several domains
1. More than 25 000 taxonomicstudies per monthi-marine.d4science.org
2. More than 60 000 species distribution maps produced and hostedi-marine.d4science.org
3. Used to build a pan- European geothermal energy mapegip.d4science.org
4. Performs cross-disciplinary social mining researchsobigdata.d4science.org
5. Enhances communication and exchange in Linguistic Studies, Humanities, Cultural Heritage, History and Archaeologyservices.d4science.org
PARTHENOS
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VREs: Social NetworkingSocial networking is key to share information in the VRE
It offers a continuously updated list of events / news produced by users and applications
User-shared News
Application-shared News
Share News
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VREs: The WorkspaceA folder-based file system allowing
managing and sharing information objects
Information objects can be
• files, dataset, workflows, experiments, etc.
• organized into folders
Users can
• Share with selected users
• disseminate via persistent public URLs
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Software Integration
Download the (python, R, Java, …) script and the user’s data
Execute script
Collect output
Destroy local copies of I/O and script
Save Output on the User’s Workspace, with provenance info
Scientist’s provided script
User’s data
Infrastructure
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Collaborative experiments
WS
Shared online folders
Inputs
Outputs
Results
Computational system
In the e-Infrastructure
Through third party software
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Scientific Workflow
Script provider
Updates the script on his private Workspace
The service downloadsthe script on-the-fly
A user executes an experiment on his/her data
The output, the input and the parameters can be shared with another user
This user can execute the experiment againand share the computation with other users
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ConclusionsVRE are defined by users and created on demand• New software can be integrated and used as-a-Service• Invoked via standard interfaces
VRE ensures • provenance management• Results on a easy-to-use storage system• Collaboration and sharing
VRE enables • Repeatability, Reproducibility and Reusability
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Visit us at www.bluebridge-vres.euTry it at i-marine.d4science.org